Local linear wavelet neural network based breast tumor classification using firefly algorithm

被引:23
|
作者
Senapati, M. R. [1 ]
Dash, P. K. [2 ]
机构
[1] Biju Patnaik Univ Technol, Dept Comp Sci & Engn, Krupajal Engn Coll, Rourkela 752002, India
[2] S O A Univ, Bhubaneswar 752020, Orissa, India
来源
NEURAL COMPUTING & APPLICATIONS | 2013年 / 22卷 / 7-8期
关键词
Local linear wavelet neural network (LLWNN); Firefly algorithm (FA); Pattern recognition; Wisconsin breast cancer (WBC); Minimum description length (MDL); TEXTURE ANALYSIS; MICROCALCIFICATIONS; SEGMENTATION; DIAGNOSIS; MASSES;
D O I
10.1007/s00521-012-0927-0
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Breast cancer is the major cause of cancer deaths in women today and it is the most common type of cancer in women. This paper presents some experiments for classifying breast cancer tumor and proposes the use of firefly algorithm (FA) to improve the performance of Local linear wavelet neural network. This work in fact uses FA to optimize the parameters of local linear wavelet neural network. The experiments were conducted on extracted breast cancer data from University of Winconsin Hospital, Madison. The result has been compared with a wide range of classifiers to evaluate its performance. The evaluations show that the proposed approach is very robust, effective and gives better correct classification as compared to other classifiers.
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页码:1591 / 1598
页数:8
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